Instructions to use bisoye/wav2vec2-base with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use bisoye/wav2vec2-base with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("audio-classification", model="bisoye/wav2vec2-base")# Load model directly from transformers import AutoProcessor, AutoModelForAudioClassification processor = AutoProcessor.from_pretrained("bisoye/wav2vec2-base") model = AutoModelForAudioClassification.from_pretrained("bisoye/wav2vec2-base", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Training in progress, epoch 8
Browse files
model.safetensors
CHANGED
|
@@ -1,3 +1,3 @@
|
|
| 1 |
version https://git-lfs.github.com/spec/v1
|
| 2 |
-
oid sha256:
|
| 3 |
size 378308536
|
|
|
|
| 1 |
version https://git-lfs.github.com/spec/v1
|
| 2 |
+
oid sha256:164146e9b162766ec450561dcdaf1b609acfd1c994b0a03e1618ba2048a0c0d6
|
| 3 |
size 378308536
|
runs/Aug28_15-25-20_ce9eb97b9f63/events.out.tfevents.1724858721.ce9eb97b9f63.36.1
CHANGED
|
@@ -1,3 +1,3 @@
|
|
| 1 |
version https://git-lfs.github.com/spec/v1
|
| 2 |
-
oid sha256:
|
| 3 |
-
size
|
|
|
|
| 1 |
version https://git-lfs.github.com/spec/v1
|
| 2 |
+
oid sha256:4c83867ac4ffdf7d3037cc8f3cac44ca2fbf8bb2141f328123909fc731e8ae83
|
| 3 |
+
size 16103
|